In this paper, we investigate how users perceive the visual quality of crowd character representations at different levels of detail (LoD) and viewing distances. Each representation, including geometric meshes, image-based impostors, Neural Radiance Fields (NeRFs), and 3D Gaussians, exhibits distinct trade-offs between visual fidelity and computational performance. Our qualitative and quantitative results provide insights to guide the design of perceptually optimized LoD strategies for crowd rendering.

翻译：本文研究了用户在不同细节层次（LoD）及观看距离下对群体角色表征视觉质量的感知。每个表征——包括几何网格、基于图像的替身、神经辐射场（NeRF）和3D高斯——在视觉保真度和计算性能之间展现出不同的权衡。我们的定性和定量结果为指导群体渲染中感知优化的LoD策略设计提供了见解。